System and method for generating markup language text templates

ABSTRACT

A method of generating a markup language text template comprises identifying a variable text element in a source language text string and assigning a first predefined symbol to the variable text element, identifying a grammatical rule for the variable text element and assigning a second predefined symbol to the variable text element based on the identified grammatical rule, determining whether to assign supplemental information to the variable text element, wherein the first predefined symbol, the second predefined symbol, and the supplemental information if assigned represent a token, and repeating the identification of a grammatical rule, assignment of first and second predefined symbols, and determination of whether to assign supplemental information for remaining variable text elements in the source language text string so as to complete a markup language text template comprising one or more tokens.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is related to U.S. patent application Ser. No.10/985,352 entitled “SYSTEM AND METHOD FOR GENERATING GRAMMATICALLYCORRECT TEXT STRINGS” and filed on Nov. 9, 2004, and U.S. patentapplication Ser. No. 10/985,338 entitled “SYSTEM AND METHOD FORGENERATING A TARGET LANGUAGE MARKUP LANGUAGE TEXT TEMPLATE” and filed onNov. 9, 2004. The disclosures of the above-described filed applicationsare hereby incorporated by reference in their entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention pertains to the field of text translation andlocalization. More particularly, the invention pertains to systems andmethods for generating grammatically correct strings in a targetlanguage based on context and a text template in a source language.

2. Description of the Related Art

Many products configured to display text to a user are used orimplemented in locales wherein the language used is different from thatof the origin of the product. For example, software applications such ascomputer games which display text to a user can translate the text foruse at the locale at which the game is being played. Similarly, it isoften desirable for Internet web pages to be presented to a user intheir language of choice, where the text of the web page was originallywritten in a different language.

Localization of text typically includes translation of a word or phraseby persons familiar with the source language and target language.However, these translators often lack the contextual information theyneed to provide a grammatically correct translation. For example,translators often use the equivalent of s/he, his/her, and ambiguouspassive voice to avoid contextual problems, resulting in a generic ifnot awkward translation. Unfortunately, grammatical rules are toocomplex and variable for totally automated software, and softwareapplication writers have a different knowledge and focus from thatneeded for localization of text.

Localized products with generic and awkward translations degrade theinternational user experience and reduce the overall quality of theproduct. This poor quality impedes penetration of international marketsand leads to lost revenue potential for the product. Some attempts havebeen made at pure machine translation. However, machine translation iscostly in terms of the required processing power and unsatisfying inoutput quality. In addition, pure static text without any variablecontent is inflexible. Static text for all possible alternatives istypically expensive, and the quality of the translation suffers by notbeing specific when there are too few alternatives.

Thus, a text localization tool which generates grammatically correcttext in a target language is needed in the technology.

SUMMARY OF CERTAIN INVENTIVE EMBODIMENTS

One embodiment of a method of generating a markup language text templatecomprises identifying a variable text element in a source language textstring and assigning a first predefined symbol to the variable textelement, identifying a grammatical rule for the variable text elementand assigning a second predefined symbol to the variable text elementbased on the identified grammatical rule, and determining whether toassign supplemental information to the variable text element, whereinthe first predefined symbol, the second predefined symbol, and thesupplemental information if assigned represent a token. The methodfurther comprises repeating the identification of a grammatical rule,assignment of first and second predefined symbols, and determination ofwhether to assign supplemental information for remaining variable textelements in the source language text string so as to complete a markuplanguage text template comprising one or more tokens.

The supplemental information may comprise an address corresponding to asource of additional information for modification of the variable textelement. A variable text element may be a verb, wherein the supplementalinformation for the verb variable text element may comprise at least oneof gender, count, age, formality, and faction of the verb subject. Thesupplemental information for the verb variable text element may comprisedefault information, and the default information may comprise masculinegender, singular count, first person speech, and normal faction.

The variable text element may be an adjective, and the supplementalinformation for the adjective variable text element may comprise atleast one of gender, grammatical case, and count of a noun beingmodified by the adjective and the grammatical case for that noun'spositioning in the text string.

The supplemental information may comprise a command to modify thevariable text element, and the command may comprise at least one ofcapitalization, first person speech, second person speech, third personspeech, accusative speech, nominative speech, past tense, present tense,future tense, participle form, and infinitive form.

The first predefined symbol may comprise an alphanumeric character, andthe first predefined symbol may correspond to one of an actor, a target,a pet of a current actor, a master of a current actor, a numberedargument, and a pointer.

The second predefined symbol may correspond to one of a noun, a verb, anadjective, a nominative pronoun, an accusative pronoun, a dativepronoun, a reflexive pronoun, a possessive adjective, an indefinitearticle, a definite article, a count, and genitive form of a noun.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a block diagram of one embodiment of a system implementing atext translation tool.

FIG. 2 is an illustration of one embodiment of a client computer coupledto a plurality of peripheral devices and a network for implementation inthe system of FIG. 1.

FIG. 3 is a block diagram of one embodiment of a client computer of FIG.1 including a translation module.

FIG. 4 is a block diagram of one embodiment of a server of FIG. 1implementing a translation module.

FIG. 5 is a block diagram of one embodiment of the translation module ofFIGS. 3 and 4.

FIG. 6 is a flowchart illustrating one embodiment of a method ofgenerating the text translation tool.

FIG. 7 is a flowchart illustrating one embodiment of a method ofgenerating a translation markup language (TML) text template in a sourcelanguage based on a text string in a source language.

FIG. 8 is a flowchart illustrating one embodiment of a method ofgenerating an accurate TML text template and metadata in a targetlanguage based on a TML text template and metadata in a source language.

FIG. 9 is an illustration of one embodiment of a translator interfacefor generating an accurate TML text string in a target language based ona TML text string in a source language.

FIG. 10 is a flowchart illustrating one embodiment of a method ofgenerating and displaying a grammatically correct text string in atarget language based on context and a TML text template in a sourcelanguage.

DETAILED DESCRIPTION OF CERTAIN INVENTIVE EMBODIMENTS

The following detailed description is directed to certain specificembodiments of the invention. However, the invention can be embodied ina multitude of different ways as defined and covered by the claims. Inthis description, reference is made to the drawings wherein like partsare designated with like numerals throughout.

The system is comprised of various modules, tools, and applications asdiscussed in detail below. As can be appreciated by one of ordinaryskill in the art, each of the modules comprises various sub-routines,procedures, definitional statements and macros. Each of the modules aretypically separately compiled and linked into a single executableprogram. Therefore, the following description of each of the modules isused for convenience to describe the functionality of the preferredsystem. Thus, the processes that are undergone by each of the modulesmay be arbitrarily redistributed to one of the other modules, combinedtogether in a single module, or made available in, for example, ashareable dynamic link library.

The system modules, tools, and applications may be written in anyprogramming language such as, for example, C, C++, BASIC, Visual Basic,Pascal, Ada, Java, HTML, XML, or FORTRAN, and executed on an operatingsystem. C, C++, BASIC, Visual Basic, Pascal, Ada, Java, HTML, XML andFORTRAN are industry standard programming languages for which manycommercial compilers can be used to create executable code.

FIG. 1 is a block diagram of one embodiment of a system 10 implementinga text translation tool, The system 10 comprises a plurality of clients16A-D and a plurality of servers 18A-C coupled to a network 20. Thenetwork 20 may include one or more of the following: Internet, Intranet,Local Area Networks (LAN) or Wide Area Networks (WAN). In the system 10,each of the clients 16A-D includes a software application 22A-D having arespective text translation tool 24A-D. The translation tools 24A-D areconfigured to generate grammatically correct text strings in a targetlanguage based on a text template and context in a source languageprovided by the software application 22A-D.

Alternatively or in addition to the text translation tools 24A-D at theclients 16A-D, the servers 18A-C may include text translation tools26A-C which function in the same or a similar manner to the texttranslation tools 24A-D at the clients 16A-D. As will be discussed infurther detail hereinafter, grammatically correct text strings may begenerated by the translation tools 24A-D at the clients 16A-D, by thetranslation tools 26A-C at the servers 18A-C by communicating over thenetwork 20, or a combination thereof.

In the system 10 illustrated in FIG. 1, one of the servers is designatedthe development server 18C. The development server 18C includes aplurality of components used to develop and update of translation tool26C at the development server 18C. The components include a text markuplanguage (TML) interface 30 which is used to generate a source languageTML text template 32 and source language metadata 34 based at least inpart on variable elements of a source language text string. As referredto herein, a TML text template is a text template comprising one or moretokens which represent words or phrases in a text string. Thetranslation tool 26C, 24A-D is configured to parse and expand the TMLtext template to a text string according to context and metadataprovided by the software application 22A-D.

Still referring to the development server 18C, a translator developmenttool 36 is used in conjunction with the source language TML texttemplate 32 to generate a corresponding target language TML texttemplate 38, target language metadata 40, and one or more targetlanguage grammatical rules 42. As will be discussed in further detailhereinafter, the translation tool 26C uses the source language TML texttemplate 32, the source language metadata 34, and the correspondingtarget language TML text template 38 and target language metadata 40 togenerate a grammatically correct text string 44 in the target language.In one embodiment, updated or new target language TML text templates andcontext are provided to the clients 16A-D from one or more of theservers 26A-B via the network 20 periodically.

FIG. 2 is an illustration of one embodiment of a client 16 coupled to aplurality of peripheral devices and a network for implementation in thesystem 10 of FIG. 1. The client 16 comprises a display 202 coupled to acomputer 204, and the computer 204 is coupled to the network 20. Aplurality of user input devices may be coupled to the computer 204, suchas a keyboard 206 and a mouse 208, The user input devices may alsoinclude a touchscreen, joystick, trackball, and microphone, for example.The peripheral devices may be coupled to the computer 204 via wired orwireless connections, and the computer 204 may be coupled to the networkvia a wired or wireless connection. As will be appreciated by thoseskilled in the technology, the client 16 as described herein is notlimited to the device illustrated in FIG. 2, but may be, for example, apersonal digital assistant (PDA), cellular telephone, pager, or anycomputing device configured to display text to a user.

FIG. 3 is a block diagram of one embodiment of the client 16 as coupledto the network 20. The client 16 comprises a display module 302configured to facilitate display of text at a display such as thedisplay 202 illustrated in FIG. 2. The client 16 further comprises asource database/memory 304 and a software module 306, wherein thesoftware module 306 is configured to coordinate and controlcommunications with the network 20. In one embodiment, the softwaremodule 306 and source database/memory 304 implement the softwareapplication 22A-D of the system 10 illustrated in FIG. 1. The softwaremodule 306 is also configured to communicate with the display module 302in order to coordinate and control display of text at the client 16display. The client 16 also includes a translation module 308 incommunication with the software module 306, wherein the translationmodule 308 is configured to generate grammatically correct text in atarget language based at least in part on information provided by thesoftware module 306 in a source language. Accordingly, the memory 304 isconfigured to store information in a source language for use by thesoftware module 306 in conjunction with the translation module 308. Theclient 16 further comprises a target database/memory 310 incommunication with the translation module 308. The targetdatabase/memory 310 is configured to store information in a targetlanguage for use by the translation module 308 in generatinggrammatically correct text strings in the target-language. In oneembodiment, the translation module 308 and the target database/memory310 implement the translation tool 24A-D of the system 10 illustrated inFIG. 1.

FIG. 4 is a block diagram of one embodiment of the server 18 as coupledto the network 20. The server 18 comprises a client communication module402 configured to coordinate and control communications with the clientor plurality of clients 16 over the network 20. Similar to the client16, the server 18 comprises a software module 404 and a translationmodule 406, wherein the software module is configured to provide thetranslation module 406 with information in a source language, and thetranslation module 406 is configured to generate text in a targetlanguage based at least in part on the information provided by thesoftware module 406 in the source language. The server 18 furthercomprises a memory 408 or source database, configured to storeinformation in a source language and/or related information for use bythe software module 404 in providing information to the translationmodule 406 and for communicating with the client communication module402. The server 18 may also include a target database/memory 410 incommunication with the translation module 406. The targetdatabase/memory 410 is configured to store information in a targetlanguage for use by the translation module in generating grammaticallycorrect text strings in the target language. In one embodiment, thetranslation module 406 and the target database/memory 410 implement thetranslation tool 26A-B of the system 10 illustrated in FIG. 1.

As will be appreciated by those skilled in the technology, thedescription and illustration of the client 16 and server 18 areexemplary in nature and are not an exhaustive description of therespective components. In addition, components of the client 16 orserver 18 may be combined, such as the source database/memory 308 andthe target database/memory 310 at the client.

FIG. 5 is a block diagram of one embodiment of a translation module 500which may be implemented as the translation module 308 at the clientand/or the translation module 406 at the server 18. The translationmodule 500 comprises a translation application interface 502 configuredto receive a TML text template in a source language and context for thetext template in the source language from a software module executing aprogram such as a game. The translation application interface 502 isfurther configured to output a grammatically correct text string in thetarget language. The translation module 500 further comprises alocalization engine 504 in communication with a translation markuplanguage lookup module 506, which is in communication with a memorycache 508 and/or a database 510. The database 510 is configured to storea plurality of TML text templates in a source language and correspondingTML text templates in a target language, and context in the sourcelanguage and corresponding context in a target language.

The localization engine 504 and the TML lookup module 506 are configuredto look up the source language TML text template and context in thememory cache 508 or the database 510 and obtain the corresponding texttemplate and context in the target language. The localization engine 504is further configured to apply the target language context to the TMLtext template using metadata, and to expand the target language templateaccording to target language grammar rules coded into the localizationengine 504. The expanded target language template is output from thetranslation module 500 via the translation application interface 502 asa text string in the target language. One embodiment of a method ofoperation of the translation module 500 is discussed in further detailhereinafter in reference to FIG. 10.

FIG. 6 is a flowchart illustrating one embodiment of a method 600 ofgenerating target language TML text templates for use by the translationmodules 308, 406 at the client 16 and/or server 18. The method 600 maybe performed manually or it can be automated, or the method may beperformed with a combination of manual and automated processes. In astep 605, a TML text template is created in a source language includingsource language text and metadata using the TML interface 30, forexample (see FIG. 1). In one embodiment, step 605 comprises a pluralityof process steps which are discussed in more detail hereinafter withrespect to FIG. 7. In a step 610, the metadata in the source language istranslated to metadata in a target language using the translatordevelopment tool 36, for example. In a step 615, the source language TMLtext template is translated to a TML text template in the targetlanguage using the translator development tool 36, for example. In oneembodiment, each of the steps 610 and 615 comprise a plurality ofprocess steps which are discussed in more detail hereinafter withrespect to FIG. 8. Finally, in a step 620, the translated or targetlanguage TML text template and target language metadata are stored foruse by a target language localization engine, such as the localizationengine 504 (see FIG. 5).

FIG. 7 is a flowchart illustrating one embodiment of a method 700 ofgenerating a translation markup language (TML) text template in a sourcelanguage based on a text string in a source language. The method 700 maybe performed manually or it may be automated, or may comprise acombination of manual and automated processes. In one embodiment, themethod 700 corresponds to step 605 of the method 600. The method 700begins in a step 702 and proceeds to a step 704 wherein a variable textelement in a text string is identified. The following text string willbe used as an example to illustrate the method 700:Emperor Crush Pierces You for 23 Points of Damage

Instead of storing a text string for every possible combination oftargets (Emperor Crush) and number of points of damage in memory, a texttemplate can be generated in TML and parsed according to the target andnumber of points. According to the method 700 and step 704, the target(Emperor Crush) in the example text string can be identified as avariable text element. In a step 706, a grammar rule for the variabletext element is identified and a token operator is assigned to thevariable text element. According to one embodiment, a plurality ofsymbols are designated as token operators, wherein each symbolcorresponds to a predefined grammar rule. For example, the followingsymbols can be predefined to correspond to the designated grammar rulesfor a variable text element:

$: name (Bob) or base text

{tilde under ( )}: proper possessive (Bob's)

%: subject pronoun (I-you-he/she/it-we-you-they)

#: object pronoun (me-you-him/her/it-us-you-them)

&: possessive pronoun (my-your-his/her/its-our-your-their)

=: direct address (sir/sire/milord-madame/madam/milady)

+: count/number of the objects

<: indefinite article (a/an/some)

>: definite article (the)

*: used for locales other than the source locale

˜: used for locales other than the source locale

In one embodiment, the above symbols are given their normal characterrepresentation when doubled. For example, when a text string requiresdisplay of the symbol “$” the symbol is written in the TML text templateas “$$”.

According to the example text string, the identified variable textelement “Emperor Crush” is a name and would therefore be assigned thetoken operator $ in step 706. Following assignment of a token operatorin step 706, the method 700 proceeds to a step 708 wherein the variabletext element is analyzed to identify the context type for the variabletext element and assign a corresponding token operand. For example, thecontext type may comprise one of actor, target, pet, master, currentspeaker, current listener, numbered argument, or pointer. Each contexttype may be assigned a corresponding symbol, such as an alphanumericcharacter. The following is an exemplary list of symbols andcorresponding context types:

0-9: numbered argument

A: the actor, the primary entity that is calling this

T: the target of the current actor

P: the pet of the current actor

M: the master of the current actor

S: the current speaker (pointing to [A, T, P, M, 0-9])

L: the current listener (pointing to [A, T, P, M, 0-9])

@: a this pointer (A if called as actor, T as target, etc.)

For the example text string, the context type of the variable textelement “Emperor Crush” is a target. Thus, according to the aboveexemplary symbol definitions, the variable text element would beassigned the token operand “T”. Thus, upon completion of step 708 in themethod 700 for the example text string, the partially formed TML texttemplate would be as follows:$T Pierces You for 23 Points of Damage

In one embodiment, if the token operand (A, T, P, M, S, L) iscapitalized, such as in the example text template, the first characterof the expanded token is force capitalized. If the token operand islower case (a, t, p, m, s, l), the case of the expanded token isunchanged. For example, for the token “$a” when a=“Boomba”, the expandedtoken retains the original capitalization.

Following assignment of the token operand in step 708, the variable textelement is analyzed in a step 710 to determine whether supplementalinformation should be assigned. In one embodiment, supplementalinformation may include at least one of supplemental details andsupplemental directives. Supplemental details provide details such asgender or count information specified by another operand, identificationof conversational roles such as first person, second person, or thirdperson, and a supplemental directive directs the localization engine 504to grammatical rules for the target language stored in memory.Directives are less applicable where the source language is English, butbecome more useful in a target language such as German. Directives mayoverride the count or gender for a variable text element, and can forcecapitalization of the variable text element. Force capitalizing fornumbered token operands can be accomplished using supplementalinformation to form an extended token. Supplemental information may bedesignated with a symbol such as “|”, and the supplemental symbolfollowed by any of the characters A, T, M, P, S, L, 0-9 directs thelocalization engine 504 to that source (A, T, M, P, S, L, 0-9) to obtaincontext for the expansion of the current token. In one embodiment, thesymbol “|” followed by a parenthesis “(” introduces a directive.Supplemental information is discussed in more detail below in referenceto step 720 of the method 700.

If it is determined in step 710 that no, the variable text element doesnot need supplemental information, then the method proceeds to a step712 where the variable text element can be identified as a basic token.The method 700 then proceeds to a step 714 wherein the text string isanalyzed to determine whether there are any remaining variable textelements undefined with a token. If it is determined in step 714 thatno, there are no remaining variable text elements, then the method 700proceeds to a step 716 where the completed TML text template is storedin memory, such as the source database/memory 304 of the client 16 (FIG.3), and the method ends in a step 718.

If it is determined in step 714 that yes, there are remaining variabletext elements in the text string which are undefined with tokens, themethod 700 returns to step 704 wherein the next variable text element inthe text string is identified. For the example text string, the analysisin step 714 would result in the determination that yes, there areremaining variable text elements undefined. The method 700 would thusreturn to step 704 and identify the next variable text elements as “23points”. The number “23” is the count for the quantity of the base text,which is “point” in this example. According to the above exemplarygrammar rule symbol assignments, the token operator for the count is “+”and the token operator for the base text point is “$”. Because thevariable text element “23 points” is neither the actor, target, pet,master, current speaker, or current listener, the base text “point” isassigned a single digit numbered argument token operand according to theabove context type definitions in step 708. For example, “point” in thisexample can be assigned the numbered operand “0”. At this point in themethod 700 for the example text string, the TML text template would beas follows:$T Pierces You for +0 $0 of Damage

Where the given context is defined according to the original textstring, that is where “T” is defined as “Emperor Crush” and “0” isdefined as “point” with a count of 23, supplemental information wouldnot be needed instep 710 for this text string and the method wouldproceed to step 712 where the tokens are identified as basic tokens. Instep 714, because there are no remaining text variable elements in theexample text string, the method proceeds to step 716 wherein the aboveTML text template is stored in memory, such as the sourcedatabase/memory 304 of the client 16 (FIG. 3). The method 700 ends in astep 718.

In one embodiment, the base text for each token operand is singular, andthe localization engine 504 generates the plural form of the text asneeded. In one embodiment, the standard rules for pluralization arebased on the last letter(s) of a word and the rules are stored in memoryfor use by the localization engine 504. Pluralization rules for Englishcan be defined as follows:

Ends in Plural Such as *fe *ves (knife) *ff *ffs (skiff) *f *ves (wolf,calf) *h *hs unless “*ch” or “*sh” *ch *ches (switch) *sh *shes (bush)*o *oes unless “kangaroo”, “piano”, “studio”, or “zoo” *s *ses (glass)*x *xes (box) *y *ies unless “*ay”, “*ey”, “*oy”, or “*uy” *ay *ays(day) *ey *eys (Turkey) *oy *oys (boy) *uy *uys (guy) *z *zes (buzz)

Some irregular words are plural by nature (scissors, police, people) andfollow irregular rules for pluralization (cactus, datum, focus). Suchirregular plurals can be handled with metadata and are discussed infurther detail hereinafter with regard to variant text.

Some base text requires an indefinite article (e.g., a, an, the) forcorrect grammar. The following text string can be used to illustrate onemethod of using indefinite articles:An Orc Pawn Pierces You for 3 Points of Damage

According to the method 700, the first variable text element isidentified in step 704, and for this example the first variable textelement would be “orc pawn”. This first variable text element can beassigned the token operator “$” in step 706 since it is standard basetext. In step 708, the variable text element “orc pawn” can be assignedthe token operand “t” because it is the target. In one embodiment, themethod 700 may include the addition of an indefinite article token tothe text template. In the present example, where the target is an orcpawn, the indefinite article token operator “<” is assigned, and thetoken operand for the indefinite article is the target “T”. In responseto the indefinite article operator, the localization engine 504 analyzesthe base text of the operand “T”, which in this case is “orc pawn”, anddetermines which indefinite article to use according to a set of rulesstored in memory. In the present example, the localization expands theindefinite article token with “an” because the base text for the operandstarts with a vowel. In addition, because the operand is capitalized,the expanded token will also be capitalized to be “An”. Similarly,because the target “orc pawn” is not at the beginning of the sentenceand is not a proper noun, the text should not be capitalized.Accordingly, the token operand in the target token “$t” is notcapitalized.

Following assignment of the token operand “t” for the variable textelement “orc pawn”, the method would move to step 710 where the variabletext element and text string are analyzed to determine whethersupplemental information should be assigned. In the present example itcan be assumed that the target will not be assigned base text that isnot a proper noun, and therefore no supplemental information should beassigned in step 710. Thus, the method moves to step 712 where the tokenis defined as a basic token. In step 714, the text string has remainingvariable text elements which are undefined, so the method returns tostep 704. In step 704, the next variable text element is “point” as inthe previous example. As discussed in the previous example, the variabletext element “point” can be assigned the tokens “+0$0” to call out thecount of the base text and the base text itself. After assignment of thetokens for the variable text element “point”, the TML text template iscomplete and stored in memory in step 716.

Given the following context and text template, the localization engine504 would expand the template and output a grammatically correct textstring:

 target “orc pawn”, 1  0 “point”, 3 template “<T $t pierces you for +0$0 of damage.” output “An orc pawn pierces you for 3 points of damage.”

In one embodiment, the target tokens may comprise an article functionwherein the target base text may or may not be a proper noun. In oneembodiment, the two tokens for the indefinite article (<T) and thetarget base text ($T) can be replaced with a single token using articlefunctions. The replacement token in the present example would be “<(T)”,wherein the localization engine 504 analyzes the operand within theparenthetical to determine whether it is a proper noun in response tothe indefinite article operator “<”. If the operand within theparenthetical is not a proper noun, the localization engine 504 insertsthe appropriate indefinite article (a or an), inserts a space, and addsthe base text for the target “orc pawn”. As discussed above, where theoperand is capitalized, the first letter of the base text is forcecapitalized. For the token “<(T)”, the localization engine 504capitalizes the indefinite article (if assigned) instead of the basetext for the target. For the case where the target base text is a propernoun, such as “Emperor Crush”, the localization engine 504 suppressesthe indefinite article and does not insert a space.

In one embodiment, the localization engine 504 determines whether basetext is a proper noun according to metadata provided with the context.The use of metadata is discussed in more detail hereinafter below inreference to FIG. 8 for example. In one embodiment, proper nouns may beless common than improper nouns and therefore designating improper nounsin the context is more efficient than defining all improper nouns withtheir appropriate indefinite article in the context. In one embodiment,a proper noun is identified in context with the symbols “{np}”. Thus,given the following context and text template, the localization engine504 would expand the template and output a grammatically correct textstring:

 target “{np}Emperor Crush”, 1  0 “point”, 1 template “<(T) pierces youfor +0 $0 of damage.” output “Emperor Crush pierces you for 1 point ofdamage.”

In one embodiment, the localization engine 504 adds a definite articleand space in a manner similar to the addition of an indefinite article.As discussed above, in one embodiment the symbol “>” corresponds to adefinite article token operator. Thus, the localization engine 504 willanalyze the token operand in response to the definite article tokenoperator and determine whether the base text for the token operand is aproper noun. If the base text is not a proper noun, the indefinitearticle “the” is inserted, followed by a space, and the base text isinserted. For the following context and template wherein the target isnot a proper noun, the localization engine 504 will expand the templateand produce the appropriate output:

 target “orc pawn”, 1 template “>(T) falls silently to the ground, andlies still.” output “The orc pawn falls silently to the ground, and liesstill.”

When the target is a proper noun as identified by the provided contextmetadata ({np}), the localization engine 504 suppresses the indefinitearticle and generates the output accordingly:

 target “{np}Emperor Crush”, 1 template “>(T) falls silently to theground, and lies still.” output “Emperor Crush falls silently to theground, and lies still.”

In one embodiment, the localization engine 504 will select theindefinite article “some” when the base text for the token operand isplural, that is when the count is greater than one. For example, giventhe following context and template, the localization engine 504 willexpand the template using the context to generate the appropriate outputtext string:

 actor “Arwen”, 1  target “Boomba the Big”, 1  0 “adequate tinbreastplate”, 1 template “$T says, ‘Greetings $a, you look like youcould use <(0).’” output “Boomba the Big says, ‘Greetings Arwen, youlook like you could use an adequate tin breastplate.’”

When the context is changed such that the base text for the numberedargument has a count greater than one, the indefinite article for thetoken operand “0” will be “some” instead of “a” or “an”. For example,when the numbered argument “0” is defined as “arrow” with a count of 20,the following template is expanded to generate the appropriate outputtext string:

 actor “Arwen”, 1  target “Boomba the Big”, 1  0 “arrow”, 20 template“$T says, ‘Greetings $a, you look like you could use <(0).’” output“Boomba the Big says, ‘Greetings Arwen, you look like you could use somearrows.’”

The use of a modified indefinite article can be further customized forparticular counts, wherein the indefinite article inserted is “acouple”, “a few”, “several”, or “many”, for example, depending on thecount of the token operand.

In the event more information about a variable text element is needed inorder to accurately expand a token, supplemental information can beprovided in addition to the token operator and operand to form anextended token in a step 720 of the method 700. In one embodiment, adesignated symbol is defined as a supplemental operator. For example,the symbol “|” can be designated the supplemental operator for the TML.As discussed briefly above, supplemental information can be details suchas missing gender or count information from another variable textelement, identification of conversational roles such as second personverb forms, and the supplemental information may include directives totarget language grammatical rules stored in memory.

Directives can override the count (ct=) or gender (sx=), or forcecapitalization (cap) in output text. In one embodiment, both the countand gender can be overridden together off another object (obj=). In oneembodiment, the capitalization directive is only needed for capitalizingnumbered arguments where there is no way to capitalize the token operandsymbol (0-9). Directives may be more useful in target languages otherthan English. Where the target language is German, for example, thedirective list may include the directive “acc” to command use ofaccusative cases and endings, “dat” to command use of dative cases andendings, “der” to command ‘der word’ endings, “gen” to command genitivecases and endings, “inf” to command the infinitive form of a verb, “neg”to command the negative form “kein” for an indefinite article or zerocount, “nom” to command nominative cases and endings, “par” to requestthe participle form of a verb, “pas” to command past tense from a verbstem, “pre” to command the present tense form of a verb stem, “rel” tocommand the relative pronoun form, “sep” to request the separable prefixfor a verb, “str” to command strong adjectival endings, “sub” to commandsubjunctive tense from a verb stem, “wea” to command weak adjectivalendings, and “wor” to command small numbers be printed as words.

The following is an example of the application of a directive whereEnglish is both the source and target language, and the directive forcapitalization is called for the numbered token operand “0” with thesupplemental operator “|”:

 0 “orc pawn”, 1, male, subhuman  1 “point”, 3 template “<0|(cap) $0pierces you for +1 $1 of damage.” output “An orc pawn pierces you for 3points of damage.”

In one embodiment, supplemental details (“$0|a”) provide missing genderand count context. In some embodiments they are most useful for verbsand phrases, but can also be of use for articles and direct address. Fora verb, supplemental details provide gender and count of the sentencesubject. In one embodiment, the default is male, singular, normalstatus, and third person. For a phrase, the supplemental details showgender and count to be selected. In one embodiment, the default is malesingular. For an adjective, some target languages require the gender andcount of the noun to determine the adjective ending. Supplementalinformation provides direct address tokens (=) with additionalinformation if the viewpoint is not that of the speaker. Supplementalinformation for indefinite article tokens (<) provides information ifthe operand is an adjective, and the count comes from the noun, which isanother variable text element.

For example, if a verb is assigned to numbered argument 1, then theextended token “$1|t” instructs the localization engine 504 to look tothe target to determine whether the subject is plural (“he buys” vs.“they buy”). The extended token “$1|S” identifies that the speaker istalking in the first person (“I buy” or “we buy”). Similarly, theextended token “$1|L” identifies the speaker is addressing the listenerin the second person (“you buy”). Verb forms vary more widely for sometarget languages other than in English.

The designations for speaker and listener are slightly differentmetadata, wherein they identify conversational roles and which tokenoperand (target, master, pet, numbered argument) is the speaker andwhich is the listener. For example, if the target is speaking, manytokens containing the speaker operand “S” are the same as tokenscontaining the target operand “T”. For example the token “$S” isequivalent to the token “$T”, the token “+S” is equivalent to the token“+T”, the token “<S” is equivalent to the token “<T”, etc. However, whenthe speaker uses the pronoun for himself/herself, the designation isfirst person, wherein the token “% s” could be parsed with “I/we”, thetoken “#s” could be parsed with “me/us”, and the token “& s” could beparsed with “my/our”, for example, depending on the count. When thespeaker uses the pronoun for the listener, the designation is secondperson wherein the tokens “% 1” and “#1” could be parsed with “you”, andthe token “&1” could be parsed with “your/your”, for example, dependingon the count. This feature is generally more useful for target languagesother than English. For example, Asian languages such as Japanese canhave a plurality of options for first and second person pronouns.

In one embodiment, the designations for speaker and listener are alsoused in selecting first and second person verb forms. Like withpronouns, when the speaker is speaking about the speaker, s/he is usingfirst person. When the speaker is talking about the listener, s/he isusing second person. These cases are discussed in more detail inreference to variant text. In some embodiments, the designations forspeaker and listener (“S” and “L”) are also used when designating formsof direct address (sir/milady). For example, the token “=L” is a tokenfor a direct address from the speaker to the listener. In certainembodiments, at least one of the station and faction of both the personbeing addressed and the person speaking make a difference as to whichdirect address is used. Table 1 is an exemplary listing for use by thelocalization engine 504 in determining which direct address to use.

TABLE 1 Station Bad faction Neutral faction Good faction Extra high YouMilord/milady Milord/milady High You Sire/madam Sire/madam Neutral YouSir/madame Sir/madame Low You Friend Champion Extra low You wormNeophyte Helper

The entries in Table 1 are based on the speaker being of a lower stationthan the listener. When the speaker is of a higher station than thelistener, the localization engine 504 will use either “sir” or “madame”for a direct address, depending on the gender of the listener. When thetranslation tool is implemented in a game, for example, using a directaddress is an opportunity to address the player more deferentially asthey advance in the game.

Similar to Table 1, a table for direct address can be provided for atarget language such as German, wherein Table 2 is an exemplary directaddress table for use by the localization engine 504 in determiningwhich direct address text to use when called by the “=” token operator:

TABLE 2 Bad faction Neutral faction Good faction Extra high FremdlingEdler Herr Edler Herr Fremde Edler Dame Edler Dame High Fremdling VerterHerr Venter Herr Fremde Verter Dame Verter Dame Neutral Fremdling MeinHerr Mein Herr Fremde Meine Dame Meine Dame Low Fremdling FreundMitstreiter Fremde Freundin Mitstreiterin Extra low Du Worm NeulingGehilfe Du Worm Neuling Gehilfin

The formation of a TML text template for the following text string willbe discussed in reference to FIG. 7 and the method 700 and illustratesthe use of supplemental information.

“Buy My Stuff!”

In the present example, the first variable text element in the textstring can be identified in step 704 as the verb “buy”. Because thevariable text element is standard base text it can be assigned the tokenoperator “$” in step 706. Because the variable text element is not anactor, target, pet, or master, it can be assigned the numbered tokenoperator “0” in step 708. When the method continues to step 710, thevariable text element is analyzed to determine whether supplementalinformation should be assigned. In the present example, since thevariable text element is a verb, the localization engine 504 willtypically need to know which verb form to use when expanding the texttemplate. The supplemental information for the verb “buy” in the presentexample would include the supplemental detail that the speaker isaddressing the listener. Accordingly, the supplemental information “|L”is assigned to the token “$0” in step 720 to form an extended token.

In addition to the supplemental information regarding the verb form, thevariable text element “buy” should be capitalized in the present examplebecause it is at the beginning of a sentence. Accordingly, thesupplemental directive “|(cap)” is added to the token for the variabletext element to form the extended token “$0|L|(cap)” for the variabletext element “buy” in the present example.

Following assignment of supplemental information to the first variabletext element to form an extended token in step 720, the text string isanalyzed in step 714 to determine whether there are remaining variabletext elements that are undefined with TML. In the present example thereare remaining undefined variable text elements, and the possessivepronoun “my” can be identified as a variable text element in step 704 asthe method returns to step 704. In step 706, the variable text elementcan be identified as a possessive pronoun and therefore assigned thetoken operator “&” in step 706 according to the exemplary definitionsabove. The context type for the variable text element is the currentspeaker and the variable text element should be lower case, thereforethe token operand “s” is assigned in step 710. Upon analysis in step710, the variable text element should not be assigned supplementalinformation and therefore is identified as a basic token in step 712.Upon analysis in step 714, there are no remaining variable text elementsundefined in the exemplary text string and the completed TML texttemplate is stored in memory in step 716.

The TML text template can be expanded with the following context tooutput a grammatically correct string. The verb syntax is discussed inmore detail hereinafter with respect to variant text and metadata.

 listener  “Boomba the Big”, 1  1  “{v}buy{ts=buys}” template“$1|L|(cap) &s stuff!” output “Buy my stuff!”

In one embodiment, where an extended token includes both supplementaldetails and supplemental directives, the supplemental details are first,followed by the directive(s) as illustrated in the above example.Extended tokens may also include a directive to look up anidentification or numbered location in memory and apply context from adefined variable text element. Phrases can also be adjusted bysupplemental details for gender and count. For example, a wanderer ofthe female gender could say “these stiletto heels are killing my feet”,while a wanderer of the male gender would say “these cowboy boots arekilling my feet”. Gender is less of a grammatical issue in the Englishlanguage than it is in other target languages.

In French and German, for example, the localization engine 504 modifiesan adjective depending on the gender and count of the noun it applies to(“$2|3”). Because such adjustments are typically not a factor when boththe source and target language are English, the use of directives ismore appropriately discussed in reference to FIG. 8 and the definitionof a target language localized template.

As discussed above, the localization engine 504 expands a TML texttemplate using context provided by the software application. The contextmay comprise a single word or combination of words, such as “FippyDarkpaw”, or the context may include metadata which provides informationabout the base text, such as “{n}Fippy Darkpaw”. In one embodiment,metadata is used to indicate default and override information for thebase text, such as the part of speech, gender, faction, rank, age, andtype of object. Overrides provided as metadata in the context of basetext can be referred to as static overrides. In one embodiment, a staticoverride is applied as the localization engine 504 applies given contextto a TML text template, and override directives in the TML text templateare applied after the static overrides during expansion of the TML texttemplate.

For example, where a target is defined as “Fippy Darkpaw”, thelocalization engine 504 will expand the token “$t” in a TML template to“Fippy Darkpaw”. However, if the software application fails to providethe localization engine 504 with a gender for Fippy, the default gendercan be set to male with the metadata “sx=m”, wherein the contextsupplied would be “{n, sx=m}Fippy Darkpaw”. The default gender providedin the static default is overridden with gender context provided by thesoftware application. However, the context can be modified to the moredefinitive “{n, sx!=m}Fippy Darkpaw” such that the gender provided bythe context metadata overrides a gender provided by the softwareapplication. The definitive static override may be particularly usefulfor target languages wherein an object is always given a particulargrammatical gender, regardless of the gender of the object in reality.For example, a ghost in German is always assigned a grammatically malegender regardless of whether the ghost is female or male.

The context can also be adjusted according to locale sensitivities. Forexample, in an Islamic nation a crusader character in a game may beunpopular. Accordingly, the honorific for a crusader can be overriddenwith the symbol “!” as follows:{n,sx=m,hn!=−2}crusader

The use of the “!” symbol in defining the honorific instructs thelocalization engine 504 to ignore context provided by the softwareapplication. As in the Fippy Darkpaw example, if the softwareapplication does not supply gender then the default male gender is used.Thus, the localization engine 504 first applies static defaults duringapplication of the context to the TML text template, then the TML texttemplate is expanded and dynamic overrides are applied, and finallystatic overrides are applied.

Defaults and overrides may be specific for each locale and targetlanguage and are stored in the target/database memory (310/410) forexample. In one embodiment, the following defaults and overrides areavailable:

1) sx or sx!—gender for that context slot

-   -   male    -   female    -   neuter (n/a, or the German neuter)    -   both (a mixed group containing both males and females)

2) ct or ct!—count for that token operand (numeric starting at 0)

3) be or be!—type of being

-   -   human    -   subhuman    -   animal    -   monster    -   undead    -   object

4) hn or hn!—honor or respect level

-   -   −2 for extra low    -   −1 for low    -   0 for normal    -   1 for high    -   2 for extra high

5) ag or ag!—age (numeric starting at 0)

In one embodiment, the first character is sufficient to set the gender(m, f, n, or b) or type of being (h, s, a, m, u, or o). More letters canbe supplied to improve readability as desired (“sx!=female”).

In one embodiment, the context contains no variants or overrides and isoptimized for speed in generating a grammatically correct text string inthe target language. The symbol “{” can be designated to indicateadditional information about the base text, as discussed above. Thus, ifthe localization engine 504 does not detect the symbol “{”, then thebase text is copied from the context definition without modification.

-   -   bone chip    -   {n}bone chip    -   {n}bone chip{pl=“bone chips”}

All three of these examples are output the same by the localizationengine 504: “bone chip” if singular and “bone chips” if plural. A firstcontext block adds or extends the metadata by adding information to thecontext. In one embodiment, the first context block ({n} for the presentexample) identifies the part of speech (e.g., noun, verb, adjective, orphrase) for the base text. The first context block may also comprise thestatic defaults and overrides for contextual data, such as gender andhonorific level discussed above. Predefined variants of the base text,such as unusual plural forms or different forms according to assignedgender, can be defined using metadata. These predefined variants can bereferred to as variant text.

The following is an exemplary list of variant identifiers for nouns,verbs and phrases:

{n} or {np}—nouns or proper nouns

f= or fem=for feminine

fs=for feminine singular

fp=for feminine plural

f3-6=for feminine, ranged plural (“a few actresses”)

f20=for feminine, specific count (“a stack of hit women”)

m= or mas=for masculine

ms=or masculine singular

mp=for masculine plural

m3-6=for masculine, ranged plural (“a few actors”)

m20=for masculine, specific count (“a stack of hit men”)

pl=for plural

si=for singular

3-6=for ranged plural (“a few spider silks”)

20=for specific count (“a stack of batwings”)

{v}—verbs

1s= or fs=for first person singular

2s= or ss=for second person singular

3s= or ts=for third person singular

1p= or fp=for first person plural

2p= or sp=for second person plural

3p= or tp=for third person plural

{p} or {pl} or {ps}—phrases; {ps} keys off speaker, {pl} keys offlistener.

f= or fem=for feminine

fs=for feminine singular

fp=for feminine plural

m= or mas=for masculine

ms=for masculine singular

mp=for masculine plural

pl=for plural

si=for singular

The singular or “si=” variants provide symmetry and can be identifiedspecifically with metadata. In one embodiment, the default or base textis the singular version of the text.

In one embodiment, the localization engine 504 uses the first contextblock identifying the part of speech, such as {n} for noun, as a basisfor parsing the variant text. The second “{ }” context block, or variantblock, recites the variant text. For example, the base text “hit man”can be assigned the following meta data:

-   -   {n, sx=male}hit man{fs=“hit woman”, fp=“hit women”, pl=“hit        men”}

The first context block identifies the base text as a noun and assigns adefault gender of male. The second text block lists the variant forms ofa “hit man” according to whether the gender is male or female, andwhether the count is singular or plural. In one embodiment, twocharacters can be used to identify the case in which the variant text isto be used. In the present example, the characters “fs” identify thecase where the gender is female and the count is singular or one, thecharacters “fp” identify the case where the gender is female and thecount is plural or greater than one, and the characters “pl” identifythe case where the count is plural or greater than one and no gender isprovided.

According to the default gender, the base text is assumed male unlessthe software application provides context to the contrary. However, ifthe software application designates that the gender is female, then thelocalization engine 504 uses the text “hit woman” if the count issingular and “hit women” if the count is greater than one. Similarly, ifthe count is greater than one and no gender information is provided, thegeneral plural text “hit men” is used. In one embodiment, thelocalization engine 504 assumes the first space or comma mark after aseries of characters indicates the end of the variant text. If thevariant text contains a single quote (′), the text is wrapped in doublequotes (″), and if the text contains a double quote (″), the text iswrapped in single quotes (′).

The simple variant text forms for nouns provide text for irregularplurals. For example, the noun “platinum” can be defined with metadataaccording to the following two examples, wherein the symbol “−” isrecognized by the localization engine 504 as an instruction to suppressaddition of characters, such as “s”, for a plural form:

-   -   {n}platinum{pl=platinum}    -   {n}platinum{pl=−}

These two contextual definitions have the same effect. Depending oncount, they could become “0 platinum”, “1 platinum”, or “10,000platinum”. The minus symbol “−” is interpreted by the localizationengine 504 as “don't add anything to form the plural”. In oneembodiment, text for the plural form of a noun may be defined byinserting an “s” or “es” after the “−” symbol in defining the pluralform, wherein the characters provided after the “−” symbol are added tothe base text to form the plural form of the noun.

Another form of variant text manages gender variants, wherein one ormore characters or symbols can be used to identify the case in which thevariant text is to be used. In the following example, the character “f”is used to identify the case in which the gender of the noun isfeminine, and the character “n” is used to identify the case in whichthe gender of the noun is male.

-   -   {n}actor{f=actress}    -   {n}actress{m=actor}

These two metadata extended context examples have the same effect,wherein localization engine 504 uses the base text “actor” unless thecontext provided by the software application indicates that the genderis feminine, in which case use the text “actress”. In the secondexample, the localization engine 504 uses the base text “actress” unlessthe context provided by the software application indicates that thegender is male, in which case the text “actor” is used. In bothexamples, the localization engine 504 will apply the standardpluralization rules after gender selection, wherein the text “actor”becomes “actors”, and the text “actress” becomes “actresses” for a countgreater than one.

Alternatively, all forms for the noun can be provided for eachcombination of gender and count scenarios. For the actor/actressexample, the metadata can be expanded as follows, and the second exampleis provided for reference:

-   -   {n}actor{fs=actress, fp=actresses, ms=actor, mp=actors}    -   {n}actor{f=actress}

As implemented, these two examples will result in the same output. Forthe first example, where the feminine singular context is provided bythe software application, the localization engine 504 uses the “fs=”variant. In the second example, the most precise variant for thefeminine singular context is the plain feminine “f=”, so thelocalization engine 504 will use the text “actress”. If instead thecontext provided by the software application is feminine plural, thelocalization engine 504 uses the “fp=” variant in the first example. Inthe second example, the most precise variant for the feminine pluralcontext is “f=”, so the localization engine 504 will use the text“actress” and use the standard pluralization rules to form the plural.

In one embodiment, metadata may include a pointer to increaseflexibility. In one embodiment, the pointer can be referred to as a‘this pointer’. A this pointer is a token with a predefined symbol asits operand, wherein the this pointer operand may be represented by thesymbol “@”, for example. In the following two examples, the numberedoperand is defined with the base text “a snake egg”. The plural form ofthe base text is defined with metadata as “+@ snake eggs”, wherein thelocalization engine 504 looks to the count context for the base text inresponse to the “+@” token in the event the count is greater than one:

 1 {n}a snake egg{pl = “+@ snake eggs”}, 1 template “Bring me $1!”output “Bring me a snake egg!”  1 “{n}a snake egg{pl = “+@ snake eggs”},7 template “Bring me $1!” output “Bring me 7 snake eggs!”

In the first example, the count for the numbered operand “1” is one, sothe singular or default version of the base text is applied to the TMLtext template and output accordingly. In the second example, the contextprovided with the numbered argument is 7, which is greater than one sothe localization engine 504 uses the plural form of the base text asdefined by the plural identifier “pl=”. According to the this pointer,the localization engine 504 outputs the count for the numbered argumentin response to the token “+@” and outputs the desired grammaticallycorrect text string.

One embodiment of the translation tool includes the use of ranged andnumbered plurals which provide more precise control over the singularand plural forms of variant text. The following example illustrates theuse of context defining different variant texts for different counts ofthe numbered argument:

 1 “{n}snake egg{1 =“a snake egg”,2 =“a couple snake eggs”,3-6=“a fewsnake eggs”,7-11= “several snake eggs”,12=“a dozen snake eggs”, 20=“astack of snake eggs”,pl=“+@ snake eggs”},20 template “Bring me $1!”output “Bring me a stack of snake eggs!”

The localization engine 504 uses the most precise variant match it canfind in the metadata, and ranged plurals are treated as more precise.Since there is a count match for 20 in this example, the localizationengine 504 outputs the text “a stack of snake eggs” for the token “$1”.If the context were 13 there is no precise match, and the localizationengine 504 would use the general plural form and output “13 snake eggs”.

In one embodiment of the translation tool, ranged plurals can also begender specific, wherein two or more characters or symbols identify thegender and count for which the variant text is to be used. In thefollowing example, the base text is “actor”, but when the gender isfeminine and the count does not correspond to one of the identifiedcounts, the localization engine 504 replaces the token with the text“actress”. In the case where the gender is feminine and the count is 2,the variant text “actress twins” is used, and when the gender isfeminine and the count is 20, the variant text “stack of actresses” isused, for example. The following two examples illustrate the use ofdifferent variant text in response to designation of a different countin the context for the numbered argument “1”.

 1 “{n}actor{fem=actress,f2=“actress twins”,f20=“stack ofactresses”,f3+=“bevy of actresses”,m2=“actor buddies”,m20=“beefcakestack”, m3+=“rat pack”}, 19, female template “Beware the evil $1!”output “Beware the evil bevy of actresses!”  1 “{n}actor{fem=actress, f2= “actress twins”,f20 = “stack of actresses”,f3+ = “bevy ofactresses”,m2 = “actor buddies”,m20 = “beefcake stack”,m3+ = “ratpack”}, 20, female template “Beware the evil $1!” output “Beware theevil stack of actresses!”

In one embodiment, the localization engine 504 uses the first varianttext match it finds in the variant text identifiers. Where the count is19, the first feminine variant match for the above example is “bevy ofactresses”, and the localization engine 504 uses this text to parse thetoken “$1”. Where the count is 20, the “f20=” identifier was asuccessful feminine match before the localization engine 504 reached themore broad identifier “f3+=”, so the localization engine 504 stopped atthe “f20=” identifier and used the defined variant text. In the casewhere the gender provided by the software application is male, thelocalization engine 504 would have supplied “rat pack” and “beefcakestack” in each example, respectively.

For verbs, there are typically six variants for the English language andmore or less for other target languages. In one embodiment, the variantverb forms comprise first, second, and third person for each a singularand plural form. Each of the variant forms of a verb can be defined withmetadata, or the most common verb form can be used as the default orbase text and the uncommon or different forms defined specifically asvariant text. The following is an example of three different methods ofdefining variant forms for the verb “buy” such that the appropriate formof the verb is used to parse a TML text template:

{v}buy{1s=buy,2s=buy,3s=buys,1p=buy,2p=buy,3p=buy}{v}buys{1s=buy,2s=buy,1p=buy,2p=buy,3p=buy} {v}buy{3s=buys}

These three methods have substantially the same effect when implementedby the localization engine 504. If a specific form is missing from thevariants, the localization engine 504 uses the default base text. Inthis example, “1s” identifies the first person singular variant text,“2s” identifies the second person singular variant text, “3s” identifiesthe third person singular variant text, “1p” identifies the first personplural variant text, “2p” identifies the second person plural varianttext, and “3p” identifies the third person plural variant text. For theverb “buy”, the conjugation is the same except for the third personsingular case. Accordingly, as illustrated in the last method, only thethird person singular variant text needs to be defined.

In English, for example, forms of a verb are most likely to vary betweenthird person singular and third person plural. The following is anexample where the third person singular form of the verb “cost” isdefined with metadata, wherein the context for the verb is based on thetarget of the template, and wherein the target is a noun with a singularcount.

 target “{n}a snake egg{pl=“+@ snake eggs”}, 1  1 “{v}cost{3s=costs}”  2“{n}platinum{pl=−}”, 3 template “ST $1 |t +2 $2.” output “A snake eggcosts 3 platinum.”

In the present example, the localization engine 504 determines that thethird person singular form of the verb “cost” should be used, and thethird person singular form is defined with metadata as “costs”.Accordingly, the “$1|t” token is parsed with the verb text “costs”. Inthe following example, the count of the target is increased to 20, andtherefore the third person plural form of the verb “cost” should beused.

 target “{n}a snake egg{pl=“+@ snake eggs”}, 20  1 “{v}cost{3s=costs}” 2 “{n}platinum{pl=−}”, 60 template “ST $1 |t +2 $2.” output “20 snakeeggs cost 60 platinum.”

Because the third person plural identifier does not appear in themetadata, the localization engine 504 uses the default or base text forthe verb, which in this case is the correct form for third personplural.

As discussed above, the translation tool can include a lookup table inone embodiment, wherein base text in addition to metadata and context isstored in a table in memory, such as the source/database memory(304/408), with a numbered or alphanumeric address. In one embodiment,the lookup table is a numbered list of text strings, wherein the textstrings are a glossary of available text for use by the softwareapplication in providing context to the translation tool. The contentsof the glossary can be modified, wherein the modification is propagatedthroughout the use of the glossary in both the software application andthe translation tool. The lookup table can comprise phrases, forexample, where phrases allow some of the same gender and count variantsas nouns. In addition, phrases in the lookup table may also includetokens for parsing and expansion by the localization engine 504.

The localization engine 504 is directed to the lookup table with apredefined token operator, such as the symbol “\”, and the token operandis the address or identification of the specific table location wherethe base text or phrase is stored. In the following example, a phrase isstored in the lookup table at address “413”, wherein a variant phrase isdefined for the case wherein the context pointed to designates thefemale gender. The localization engine 504 needs additional informationto parse the template phrase from the lookup table, so the supplementalinformation “|L” instructs the localization engine 504 to use thecontext provided for the listener in parsing the template phrase fromthe lookup table.

 \413 “{p}Attacking <(t), master.{f= “Attacking <(t), mistress.”}” target “orc pawn”, 1, male, subhuman  listener “Galadriel”, 1, female,human template “\413|L” output “Attacking an orc pawn, mistress.”

In the above example, the gender context provided for the listener isfemale, therefore the localization engine 504 uses the variant phraseidentified for the female gender at the lookup table address “413”, andparses the template for the variant phrase according to the contextprovided for the target.

 \413 “{p}Attacking <(t), master.{f= “Attacking <(t), mistress.”}” target “orc pawn”, 1, male, subhuman  listener  “Gandalf”, 1, male,human template “\413|L” output “Attacking an orc pawn, master.”

In this example, the gender context provided for the listener is male,therefore the localization engine 504 uses the base text or defaultphrase at the lookup table address “413”, and parses the default phrasetemplate using the context provided for the target.

Supplemental information used in conjunction with the lookup table isnot limited to supplemental details, and supplemental directives mayalso be used. For example, the extended token “\413|(sx=f)” instructsthe localization engine 504 to select the female gender version of thephrase stored at the lookup table address “413”. Generally, “sx=”, “ct=”and “obj=” directives can be applied to nouns and phrases to commandselection of particular variants.

In one embodiment, two types of phrases are defined because they arecommonly used, The first type of phrase is identified with the metadata“{ps}” and is a phrase wherein the gender and count are taken from thecontext of the speaker. The second type of phrase is identified with themetadata “{pl}” and is a phrase wherein the gender and count are takenfrom the context of the listener. The invocation syntax for thesephrases is simpler (“\414|” rather than “\414|L”) than standard phrases({p}) because no supplemental details (the “|L”) are needed. A secondarybenefit of these predefined phrases is that they are more easilysubstituted in conjunction with other text that does not require thesupplemental details. The following is an example of a use of thelistener based phrase ({pl}) in combination with the lookup table.

 \414 “{pl}Attacking <(t), master. {f= “Attacking <(t), mistress.”}” target “orc pawn”, 1, male, subhuman  listener  “Galadriel”, 1, female,human template “\414” output “Attacking an orc pawn, mistress.”

In this example, the result is the same as when the basic phrase ({p})was used in combination with the supplemental details, but the TML texttemplate is shorter because the supplemental information instructing thelocalization engine 504 to use the context of the listener is removedfrom the template.

The following are two additional examples of the use of the {ps} and{pl} metadata wherein the two examples use the same TML text templatebut produce different results depending on the context:

 speaker  “Bob”  listener  “Jane”, female  0  “\414”  \414  “{ps}I toremy shirt{f=‘I tore my dress’}” template “$S says, ‘$0’.” output “Bobsays, ‘I tore my shirt.”’  speaker  “Fido”  listener  “Jane”, female  0 “\415”  \415  “{pl}My master $L loves me{f=‘My mistress loves me’}”template “$S says, ‘$0’.” output “Fido says, ‘My mistress Jane lovesme.”’

In the above examples, the same template can be used where the genderand count to be used for the token “$0” are referenced to either thelistener or the speaker, and such designation does not need to appear inthe TML text template in the “$0|L” or the “$0|S” form.

The TML text templates generated according to the method 700 of FIG. 7and metadata in a source language generated according to the abovemethods are used by translators to generate an accurate TML texttemplate and metadata in a target language. FIG. 8 is a flowchartillustrating one embodiment of a method 800 of generating an accurateTML text template and metadata in a target language based on a TML texttemplate and metadata in a source language. In one embodiment, themethod 800 is implemented using the translator development tool 36 (FIG.1), which provides a translator interface such as the interfaceillustrated in FIG. 9. In one embodiment, the method 800 implements theprocess steps 610 and 615 of the method 600 of FIG. 6. The method 800may be performed manually or it may be automated, or the method maycomprise a combination of both automated and manual processes.

Referring to FIG. 8, the method begins at a step 802 and proceeds to astep 804 wherein the translator receives one or more source language TMLtext templates and associated base text and metadata. The following isan exemplary source language TML text template and exemplary base textand metadata:

 0 “gauntlet”, 2, object, normal  1 “beautiful”, 0  2 “silver”, 0template “You buy <1 $1 $2 $0”

In one embodiment, the source language TML text template and associatedmetadata are provided in a chart or table, each with a predefinedaddress. Following receipt of the source language TML text template andassociated base text and metadata in step 804, the translator translatesthe base text and adds and modifies the metadata as necessary for thetarget language. In the present example the target language is French,and the source language metadata can accordingly be modified in step 806and base text translated as follows to define variant forms of the basetext and a default gender:

0 “{n, sx=m}gantelet{ }, 2, object, normal 1 “{ap}beau{ma=bel, fs=belle,fp=belles}”, 0 2 “{a}argenté{ }”, 0

As discussed above, the part of speech for a word assigned to a numberedargument is designated with metadata in the context. In a number oflanguages, such as French, the order of a noun and one more adjectivesmay not be grammatically correct if the order from the English templateis used. Thus, the part of speech designations {n}, {ap}, {a} are usefulfor some locales in generating grammatically correct text. An additionalvariant text identifier is used in the context for the numbered argument“1” in the present example which is particular to the French targetlanguage. Specifically, the identifier “ma” designates the masculineaspire form of the adjective “beau”, that is the form when the adjectiveis placed in front of a masculine noun that begins with a vowel or mute“h”. Additional variant text identifiers may be used for each targetlanguage that are unique to that target language, or identifiers commonto some locales may also be used.

Following addition and modification of metadata in step 806, thetranslator translates words or phrases in the TML text template in astep 808. In the present example, the translator translates the phrase“You buy” to “Vous achette” for the French target language in step 808.Following translation of words or phrases in the TML text template tothe target language in step 808, the translator uses the translated basetext and modified metadata to define a target language localizedtemplate for the source language TML text template in a step 810. InFrench, adjectives must match case with the gender and count of the nounwhich they modify, and placement of an adjective with respect to a nounmay depend on the meaning of the adjective. Accordingly, the translatordefines a target language localized template that reflects this rule.

In one embodiment, a macro can be used to define the target languagelocalized template, wherein the macro is an extended token comprising apredefined token operator such as the symbol “\” and supplementalinformation. In one embodiment, a macro is used by the localizationengine 504 to implement a localized grammatical rule coded into thelocalization engine 504. For example, a macro “\noun( . . . )” can beused to invoke a rule that orders adjectives around a noun according toaccurate French grammatical rules. Such a rule may be coded into thelocalization engine for the French target language, for example. In thepresent example, the macro would be defined as “\noun($0, $1, $2),wherein the first argument within the parenthetical can be assumed thenoun, and all remaining arguments are adjectives.

Following definition of the target language localized template in step810, the token or tokens with supplemental information are applied tothe target language localized template using grammatical rules in a step812. For the present example, the translator would define the followingtarget language localized template by applying the macro extended tokento the localized template in step 812:

-   -   template “Vous achette \noun($0, $1, $2)”

In the present example, the macro token is applied to the targetlanguage localized template according to French grammatical rules,wherein the translator development tool analyzes the modified metadatafor the numbered arguments “1” and “2” to determine the type ofadjective. In this example, the numbered argument “1” defines a prefixadjective and the numbered argument “2” defines a suffix adjective.According to the French grammratical rule coded at the localizationengine 504, the localization engine 504 would expand the macro andgenerate the following target language localized template:

-   -   template “Vous achette $1|0 $0 $2|0”

Following application of the extended token(s) to the target languagelocalized template in step 812, the translator verifies the accuracy ofthe target language TML text template and associated metadata in a step814. This verification can be performed using the translator developmenttool 36 and translator interface 900 illustrated in FIG. 9, for example.In the event the target language TML text template and associatedmetadata are inaccurate, the translator can modify the metadata and/orthe target language TML text template such that the TML text templateand metadata will produce a grammatically correct text string in thetarget language when expanded by the localization engine 504. Uponverification of the accuracy of the target language TML text templateand associated metadata in step 814, the method 800 ends in a step 816.

The target language TML text template and associated metadata generatedaccording to the method 900 are stored at the database 510 (see FIG. 5)in relation to their corresponding TML text template and base text inthe source language for lookup by the translation markup language lookupmodule 506. In one embodiment, the source language TML text templatesare referenced with an address instead of the template itself, and theaddress corresponds to the target language TML text templates asaddressed in the database 510.

In one embodiment, the designated grammar rules for the above definedtoken operator symbols are customized according to the needs of thelocale target language. For example, the following set of designatedgrammar rules can be applied to the same set of symbols for the Germanlocale;

$: name (Bob) or base text

%: nominative pronoun (ich/du/er-sie-es etc.)

#: accusative pronoun (mich/dich/inh-sie-es etc.)

˜: dative pronoun (mir/dir/ihm-ihr-ihm etc.)

*: reflexive pronoun (mich/dich/sich, mir/dir/sich, etc.)

&: possessive adjective (mein/dein/sein-ihr-sein etc.)

<: indefinite article (ein*/kein*/einige/viele)

>: definite article (der/die/das, den/die/das, dem/der/dem, des/der/des,etc.)

+: count/number of the objects

{tilde under ( )}: genitive form of a noun (Kunden)

=: direct address (gender & respect from context, Herr/Dame)

The translator may use this set of designated grammar rules to definethe target language TML text template.

As discussed above, the translator interface 900 of FIG. 9 may be usedin conjunction with the method 800 and particularly to verify theaccuracy of a target language TML text template and associated data. Inone embodiment, the translator interface 900 comprises a source languagetext string input section 902 configured to display a text string in asource language as input by a user. The translator interface 900 furthercomprises a variable or base text input section 904 configured todisplay variable or base text in the target language as input by a user.This variable text may include metadata.

The translator interface 900 also comprises a target language TML textstring input section 906 configured to display the target language TMLtext string defined by a user according to the method 800 illustrated inFIG. 8, for example. The translator interface 900 further comprises anargument input section 908 configured to display the current argumentfor which variable text is displayed and modified in the variable textinput section 904, wherein the current argument may be one of target,actor, pet, master, speaker, listener, or numbered argument 0-9, forexample. The translator interface 900 also includes one or more contextinput sections configured to display at least one context element asinput by the user for use in expanding the target language TML texttemplate displayed in the section 906. The one or more context inputsections may include a count input section 910, a gender input section912, a type input section 914, an honor or honorific input section 916,and a faction input section 918, for example. The input for the contextelements may be manually input by a user or chosen from a predefined setof inputs through a drop-down menu, for example.

The translator interface 900 further comprises a target language textstring output section 920 configured to display a text string in thetarget language in response to user selection of an expand pattern input922. In response to user selection of the expand pattern input 922, thetranslator development tool generates the target language text stringbased on an expansion of the target language TML text template using thevariable text defined in connection with the argument input section 908,and at least one context element from the context element input sections912, 914, 916, 918. The translator interface may further comprise asource language text input section 924, wherein the text displayed atthe input 924 is used to define the target language TML text stringdisplayed at input section 906.

The modified metadata and accurate target language TML text templatesgenerated according to method 800 are stored in memory, such as thedatabase 510 (FIG. 5) with reference to their corresponding sourcelanguage metadata and TML text template.

FIG. 10 is a flowchart illustrating one embodiment of a method 1000 ofgenerating and displaying a grammatically correct text string in atarget language based on context and a TML text template in a sourcelanguage. The method 1000 begins in a step 1002 and proceeds to a step1004 wherein the translation application interface 502 at thetranslation module 500 receives a source language TML text template andcontext as provided by the software module 306 or 404 (see FIGS. 3 and4). In one embodiment, the translation application interface 502communicates the source language TML text template and context to thelocalization engine 504. In a step 1006, the localization engine 504looks up the source language TML text template and source languagecontext in memory (cache 508 or database 510) with the assistance of theTML lookup module 506 and obtains a corresponding target language TMLtext template and context in the target language. In addition, in thecase where the context received in step 104 contains one or more tokenswith an address lookup, for example, step 1006 includes lookup of theaddress wherein the localization engine 504 obtains the contents of theaddress.

In a step 1008, the localization engine 504 applies the target languagecontext to the target language TML text template according to the texttemplate tokens using the metadata provided with the target languagecontext. In one embodiment, the localization engine 504 applies thetarget language context in reference to the source language contextaccording to rules coded into the localization engine 504. In a step1010, the localization engine 504 expands the target language TML texttemplate according to target language grammar rules stored, for example,in the cache 508 or database 510. In a step 1012, the localizationengine 504 communicates the expanded target language TML text templateto the translation application interface 502, which outputs thegrammatically correct text string in the target language in a step 1012to the software module 306 or 404, for example. In a step 1014, thedisplay module 302 at the client 16 displays the grammatically correcttext string in the target language, and the method 1000 ends in a step1016.

In some embodiments, where the grammatically correct text string isgenerated by the translation module 406 at the server 18, for example,the software module 404 communicates the grammatically correct textstring in the target language to the client communication module 402,which transmits the grammatically correct text string to the client 16via the network 20.

The following is an exemplary execution of the method 1000. Thetranslation application interface 502 may receive the following contextand text template in a source language, which in this case is English,in step 1004 of the method 1000:

 0 “gauntlet”, 2, object, normal  1 “beautiful”, 0  2 “silver”, 0template “You buy <1 $1 $2 $0”

In step 1006, the localization engine 504 looks up the source languageTML text template and source language context in memory with theassistance of the TML lookup module 506 and obtains the followingcorresponding target language TML text template and context in thetarget language, wherein the target language for the present example isFrench:

 0 “{n, sx=m}gantelet{ }, 2, object, normal  1 “{ap}beau{ma=bel,fs=belle, fp=belles}”, 0  2 “{a}argenté{ }”, 0 template “Vous achette\noun($0, $1, $2)”

In step 1008, the localization engine 504 applies the target languagecontext to the target language TML text template token using themetadata provided with the target language context. In a step 1010, thelocalization engine 504 expands the target language TML text templateaccording to the target language grammar rules, which in the presentcase are the rules for the target language French. According to theFrench grammar rules, the target language TML text template would beexpanded such that the template would be replaced with the followingexpanded template:

-   -   template “Vous achette $1|0 $0 $2|0”

In a step 1012 the localization engine 504 would output the followinggrammatically correct string via the translation application interface502:

-   -   output “Vous achette beaux gantelets argentés”

In a step 1014, the display module 302 displays this grammaticallycorrect text string in the target language, and the method ends in step1016.

As will be appreciated by those skilled in the technology, the targetlanguages and syntax described herein is exemplary in nature and do notlimit the scope of the invention. In addition, the person skilled in thetechnology would be able to implement the methods and systems describedherein in a plurality of implementation environments and with morecomplex or simplistic text strings and grammatical rules. Theseimplementations and varieties of text strings and grammatical rules arewithin the scope of the invention. The grammatical rules and textstrings described herein are exemplary in nature and additionallycomplex text strings and variety of locales or target languages arecontemplated. For example, the invention is not limited to Europeanlocales and may be implemented in a variety of locales where thelanguage used may be a modified form of English, such as the UnitedKingdom wherein a predefined set of words are used in place of preferredwords in English or the locale uses preferred spellings, or a languageother than English.

While the above detailed description has shown, described, and pointedout novel features of the invention as applied to various embodiments,it will be understood that various omissions, substitutions, and changesin the form and details of the device or process illustrated may be madeby those skilled in the art without departing from the spirit of theinvention. The scope of the invention is indicated by the appendedclaims rather than by the foregoing description. All changes which comewithin the meaning and range of equivalency of the claims are to beembraced within their scope.

1. A computer-implemented method of generating a translation markuplanguage text template in a source language, the method comprising:identifying a variable text element in a source language text string byat least one translation tool residing in at least one of a clientcomputer and a server computer; analyzing the variable text element toidentify a context type and assign a first predefined symbol to thecontext type of the variable text element; identifying a grammaticalrule for the variable text element; assigning a second predefined symbolto the variable text element based on the identified grammatical rule;determining whether to assign supplemental information to the variabletext element, wherein the first predefined symbol, the second predefinedsymbol, and the supplemental information if assigned represent a token;and assigning supplemental information to the variable text element whenit is determined that the supplemental information is needed toaccurately expand the token.
 2. The method of claim 1, wherein thesupplemental information comprises an address corresponding to a sourceof additional information for modification of the variable text element.3. The method of claim 1, wherein a variable text element is a verb, andwherein the supplemental information for the verb variable text elementcomprises at least one of gender, count, age, formality, and faction ofthe verb subject.
 4. The method of claim 3, wherein the supplementalinformation for the verb variable text element comprises defaultinformation.
 5. The method of claim 4, wherein the default informationcomprises masculine gender, singular count, first person speech, andnormal faction.
 6. The method of claim 1, wherein a variable textelement is an adjective, and wherein the supplemental information forthe adjective variable text element comprises at least one of gender,grammatical case, and count of a noun being modified by the adjectiveand the grammatical case for that noun's positioning in the text string.7. The method of claim 1, wherein the supplemental information comprisesa command to modify the variable text element.
 8. The method of claim 7,wherein the command comprises at least one of capitalization, firstperson speech, second person speech, third person speech, accusativespeech, nominative speech, past tense, present tense, future tense,participle form, and infinitive form.
 9. The method of claim 1, whereinthe first predefined symbol comprises an alphanumeric character.
 10. Themethod of claim 1, wherein the first predefined symbol corresponds toone of an actor, a target, a pet of a current actor, a master of acurrent actor, a numbered argument, or a pointer.
 11. The method ofclaim 1, wherein the second predefined symbol corresponds to one of anoun, a verb, an adjective, a nominative pronoun, an accusative pronoun,a dative pronoun, a reflexive pronoun, a possessive adjective, anindefinite article, a definite article, a count, and genitive form of anoun.
 12. A non-transitory computer readable medium including a programexecuting instructions to output a grammatically correct text string ina target language, the program comprising executable instructions thatcause a computer to: identify a variable text element in a sourcelanguage text string; analyze the variable text element to identify acontext type and assign a first predefined symbol to the context type ofthe variable text element; identify a grammatical rule for the variabletext element; assign a second predefined symbol to the variable textelement based on the identified grammatical rule; determine whether toassign supplemental information to the variable text element, whereinthe first predefined symbol, the second predefined symbol, and thesupplemental information if assigned represent a token; and assignsupplemental information to the variable text element when it isdetermined that the supplemental information is needed to accuratelyexpand the token.
 13. The computer readable medium of claim 12, whereinthe token further comprises supplemental information.
 14. The computerreadable medium of claim 13, wherein the supplemental informationcomprises an address corresponding to a source of additional informationfor modification of the variable text element.
 15. The computer readablemedium of claim 13, wherein a variable text element is a verb, andwherein the supplemental information for the verb variable text elementcomprises at least one of gender, count, age, formality, and faction ofthe verb subject.
 16. The computer readable medium of claim 15, whereinthe supplemental information for the verb variable text elementcomprises default information.
 17. The computer readable medium of claim16, wherein the default information comprises masculine gender, singularcount, first person speech, and normal faction.
 18. The computerreadable medium of claim 13, wherein a variable text element is anadjective, and wherein the supplemental information for the adjectivevariable text element comprises at least one of gender, grammaticalcase, and count of a noun being modified by the adjective and thegrammatical case for that noun's positioning in the text string.
 19. Thecomputer readable medium of claim 13, wherein the supplementalinformation comprises a command to modify the variable text element. 20.The computer readable medium of claim 19, wherein the command comprisesat least one of capitalization, first person speech, second personspeech, third person speech, accusative speech, nominative speech, pasttense, present tense, fixture tense, participle form, and infinitiveform.
 21. The computer readable medium of claim 12, wherein the secondpredefined symbol comprises an alphanumeric character.
 22. The computerreadable medium of claim 12, wherein the second predefined symbolcorresponds to one of an actor, a target, a pet of a current actor, amaster of a current actor, a numbered argument, and a pointer.
 23. Thecomputer readable medium of claim 12, wherein the first predefinedsymbol corresponds to one of a noun, a verb, an adjective, a nominativepronoun, an accusative pronoun, a dative pronoun, a reflexive pronoun, apossessive adjective, an indefinite article, a definite article, acount, and genitive form of a noun.
 24. The method of claim 1, whereinthe context type of the variable text element includes: a numberedargument; an actor; a target of the actor; a pet of the actor; a masterof the actor; a current speaker; or a current listener.
 25. Acomputer-implemented method of generating a translation markup languagetext template in a source language, the method comprising: identifying avariable text element in a source language text string by at least onetranslation tool residing in at least one of a client computer and aserver computer; analyzing the variable text element to identify acontext type and assign a first predefined symbol to the context type ofthe variable text element; identifying a grammatical rule for thevariable text element; assigning a second predefined symbol to thevariable text element based on the identified grammatical rule;determining whether to assign supplemental information, including atleast one of supplemental details and supplemental directives, to thevariable text element; assigning the supplemental information to thevariable text element to accurately expand a token when it is determinedthat supplemental information needs to be assigned, wherein the firstpredefined symbol, the second predefined symbol, and the supplementalinformation represent the token; and identifying the variable textelement as a basic token when it is determined that supplementalinformation does not need to be assigned.
 26. A non-transitory computerreadable medium including a program executing instructions to output agrammatically correct text string in a target language, the programcomprising executable instructions that cause a computer to: identify avariable text element in a source language text string; analyze thevariable text element to identify a context type and assign a firstpredefined symbol to the context type of the variable text element;identify a grammatical rule for the variable text element; assign asecond predefined symbol to the variable text element based on theidentified grammatical rule; determine whether to assign supplementalinformation, including at least one of supplemental details andsupplemental directives, to the variable text element; assign thesupplemental information to the variable text element to accuratelyexpand a token when it is determined that supplemental information needsto be assigned, wherein the first predefined symbol, the secondpredefined symbol, and the supplemental information represent the token;and identify the variable text element as a basic token when it isdetermined that supplemental information does not need to be assigned.